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Ant Colony Optimization for Improved Change Detection in Satellite Images
  • Snehlata Sheoran,
  • Neetu Mittal,
  • Alexander Gelbukh
Snehlata Sheoran
Amity University

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Neetu Mittal
Amity University
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Alexander Gelbukh
Instituto Politecnico Nacional
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Abstract

Monitoring of Earth surface with the help of satellite images helps in land use land cover, resource planning & management, change detection and agricultural development areas. Satellites images are great repository of information and extraction of information from these unclear images is a challenging task. In order to identify the objects and boundaries in satellite images, various digital image based processing techniques like Sobel, Canny and Prewitt have been explored in this paper. Further, Ant Colony Optimization has been used to obtain the optimized images. Hybrid techniques viz.- AC0-Sobel, ACO-Canny and ACO-Prewitt are implemented and the results are quantitatively validated with the help of entropy and PIQE values of output optimized images. The results indicates that ACO-Canny hybrid technique yields better quality satellite images as compared to ACO-Sobel, ACO-Prewitt, Sobel, Canny and Prewitt edge detection techniques.